AI and Crypto Union to Unleash $20 Trillion Economic Boost by 2030

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The potent fusion of artificial intelligence and cryptocurrency is being billed as the next big wave set to stimulate seismic growth in the global economy. Experts predict this combined force could conjure an astounding addition of $20 trillion to the worldwide gross domestic product by the close of the next decade, a recent study by Bitcoin ETF supplier Bitwise reveals.

Casting a discerning eye over this burgeoning sector, analyst Juan Leon underscores the incredible potential for market growth, anticipating a surge that will outpace most existing projections. The importance of this ongoing trend was emphasized during the annual Consensus conference held in Austin, an event that saw industry mavens debating the far-reaching pitfalls and prospects of this union, touching upon aspects like monetary policy, Bitcoin ETFs, regulation and tokenization.

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Leon points to the ascendancy of AI driven by corporate torchbearers such as Nvidia, a dynamic that has skyrocketed the market capitalization of the world’s premier AI chip producer past the $3 trillion mark. This staggering valuation has crowned Nvidia as the second-largest public company in existence on a global scale.

However, Leon cautions that this stratospheric rise is not without its drawbacks. The thirst for AI dominance has birthed what he describes as “an unprecedented shortage” of key resources such as data centers, electricity supply, and AI chips.

To maneuver through this challenge, AI corporations are aligning forces with Bitcoin miners, as they house the critical resources needed. These miners have in their arsenal the power-charged chips, superior cooling systems, and logistical support vital to process and store colossal volumes of data.

In a bid to accentuate this budding collaboration, the report by Bitwise sheds light on recent advancements in the arena, taking the acquisition bid made by CoreWeave for Core Scientific as evidence of this mutual alliance. The subsequent partnership between these firms serves to illustrate the expanding link between miners and AI suppliers.

Leon articulates that the merging of AI and cryptocurrency has far-reaching prospects which warrant exploration. One such prospect is the sphere of data validation. Deploying the secure, transparent and tamper-proof nature of public blockchains may very well serve as a significant deterrent against potential abuses of AI technology.

Innovative startups like Attestive are implementing blockchain technology to create digital trails of video content, ensuring their authenticity and battling the growing scourge of “deep fakes”. Such applications could further extend to authenticating governmental communications, academic research, and more, by providing an essential audit trail and safeguard against AI-generated material.

Leon, in his report, conjectures that this partnership might hold remarkable possibilities in the domain of virtual assistants as well. Even as AI-based helpers such as Siri and Alexa have grown leaps and bounds in their capabilities, he suggests their efficacy could be improved dramatically by infusing them with smart contracts and cryptocurrencies such as Bitcoin or stablecoins.

He argues that the marriage of these two technologies would enable the secure and efficient completion of intricate tasks. This, in turn, would amplify productivity and radically broaden the capabilities of AI-backed virtual assistants.

Looking ahead, PwC anticipates that by the year 2030, AI and cryptocurrency could contribute an impressive $15.7 trillion and $1.8 trillion respectively to the global economy. Leon, however, posits that the amalgamation of the two could generate a compounding impact, potentially pushing their combined value up to a whopping $20 trillion, or even more.

In conclusion, the convergence of AI and cryptocurrency presents a remarkable prospect for global economic expansion. The potential addition of $20 trillion to the global GDP by 2030 showcases this as a ‘megatrend’, set to revolutionize industries by tackling multiple challenges in areas like data centers, data validation, and the performance of virtual assistants.